Exploring new ways for personalized e-commerce through Digital TV

BibTex:
Áreas de investigación:	Sin categoría	Año:	2012
Tipo de publicación:	Parte de colección
Autores:	7, 2 8
Publisher:	Springer
Editor:	I. Anagnostopoulos, M. Bielikova, P. Mylonas, N. Tsapatsoulis



@incollection{newways, author = "7,8,2,9", abstract = "The evolution of information technologies is consolidating recommender systems as essential tools in e-commerce. To date, these systems have focused on discovering the items that best match the preferences, interests and needs of individual users, to end up listing those items by decreasing relevance in some menus. In this paper, we propose extending the current scope of recommender systems to better support trading activities, by automatically generating interactive applications that provide the users with personalized commercial functionalities related to the selected items. We explore this idea in the context of Digital TV advertising, with a system that provide personalized commercial functionalities, gathering contents from multiple sources and bring together semantic reasoning techniques, SWRL rules and new architectural solutions for web services and mashups.", booktitle = "Studies in computational intelligence, semantic hyper/multi-media adaptation: schemes and applications", editor = "I. Anagnostopoulos, M. Bielikova, P. Mylonas, N. Tsapatsoulis", publisher = "Springer", title = "{E}xploring new ways for personalized e-commerce through {D}igital {TV}", year = "2012", }
Abstract:	The evolution of information technologies is consolidating recommender systems as essential tools in e-commerce. To date, these systems have focused on discovering the items that best match the preferences, interests and needs of individual users, to end up listing those items by decreasing relevance in some menus. In this paper, we propose extending the current scope of recommender systems to better support trading activities, by automatically generating interactive applications that provide the users with personalized commercial functionalities related to the selected items. We explore this idea in the context of Digital TV advertising, with a system that provide personalized commercial functionalities, gathering contents from multiple sources and bring together semantic reasoning techniques, SWRL rules and new architectural solutions for web services and mashups.

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